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Modeling of Three-Dimensional RNA Structures Using SimRNA

Protocol
First Online:
Part of the Methods in Molecular Biology book series (MIMB, volume 2165)

Abstract

The molecules of the ribonucleic acid (RNA) perform a variety of vital roles in all living cells. Their biological function depends on their structure and dynamics, both of which are difficult to experimentally determine but can be theoretically inferred based on the RNA sequence. SimRNA is one of the computational methods for molecular simulations of RNA 3D structure formation. The method is based on a simplified (coarse-grained) representation of nucleotide chains, a statistically derived model of interactions (statistical potential), and the Monte Carlo method as a conformational sampling scheme.

The current version of SimRNA (3.22) is able to predict basic topologies of RNA molecules with sizes up to about 50–70 nucleotides, based on their sequences only, and larger molecules if supplied with appropriate distance restraints. The user can specify various types of restraints, including secondary structure, pairwise atom–atom distances, and positions of atoms. SimRNA can be also used for studying systems composed of several chains of RNA. SimRNA is a folding simulations method, thus it allows for examining folding pathways, getting an approximate view of the energy landscapes.

Key words

RNA structure RNA folding simulation De novo modeling Restraints supported modeling Coarse-grained models Statistical potentials Monte Carlo simulations Replica Exchange simulations 
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Notes

Acknowledgments

This work was supported by the Polish National Science Center Poland (NCN) (grant 2016/23/B/ST6/03433 to M.J.B.). T.K.W. was supported by NCN (grant 2017/25/B/NZ2/01294 to J.M.B). C.N. and J.M.B. were additionally supported by the NCN (grant 2017/26/A/NZ1/01083 to J.M.B.) and by the IIMCB statutory funds. S.M. was supported by the IIMCB statutory funds. Simulations were performed using the computational resources of IIMCB, the Poznań Supercomputing and Networking Center at the Institute of Bioorganic Chemistry, Polish Academy of Sciences (grant 312), and the Interdisciplinary Centre for Mathematical and Computational Modelling at the University of Warsaw (grant G66-9). We thank the current and former members of the Bujnicki group (in particular developers of methods and participants of the RNA-Puzzles experiment) for their intellectual contributions.

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© Springer Science+Business Media, LLC, part of Springer Nature 2020

Authors and Affiliations

  1. 1.Laboratory of Bioinformatics and Protein EngineeringInternational Institute of Molecular and Cell Biology in WarsawWarsawPoland
  2. 2.Bioinformatics Laboratory, Institute of Molecular Biology and Biotechnology, Faculty of BiologyAdam Mickiewicz UniversityPoznanPoland

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